Added plotting file

display_results.py

@@ -0,0 +1,176 @@
+import sys
+import numpy as np
+import matplotlib.pyplot as plt
+
+class Experiment:
+    def __init__(self):
+        self.name = ""
+        self.description = ""
+        self.data = []
+        self.labels = []
+
+    def extratMetadata(self, row):
+
+        if 'benchmark' in row[0]:
+            self.name = row[0].replace(":", "").replace("benchmark", "").strip()
+
+    def addRow(self, row):
+        if len(row) < 1:
+            return
+
+        if len(row) == 1:
+            self.extratMetadata(row)
+            return
+
+        try:
+            row_data = []
+            for element in row:
+                int_val = int(element)
+                row_data.append(int_val)
+            self.data.append(row_data)
+        except Exception:
+            self.labels = row
+
+    def getAverages(self):
+        if not self.isValid():
+            return
+        data_array = np.asarray(self.data)
+        averages = np.average(data_array, axis=0)
+        return averages[1:]
+
+    def getErrorRange(self):
+        if not self.isValid():
+            return
+        data_array = np.asarray(self.data)
+        averages = np.average(data_array, axis=0)
+        deltas = data_array - averages
+        abs_deltas = np.abs(deltas)
+        max_deltas = np.max(abs_deltas, axis=0)
+        return max_deltas[1:]
+
+    def isValid(self):
+        return len(self.data) > 0
+
+    def getCloned(self):
+        new_experiment = Experiment()
+        new_experiment.labels = self.labels
+        new_experiment.name = self.name
+        new_experiment.description = self.description
+        return new_experiment
+
+    def getAveragedData(self):
+        block = self.data[0][0]
+        sum = 0
+        averages = []
+        blocks = []
+        count = 0
+        for datum in self.data:
+            if block != datum[0]:
+                averages.append(sum / count)
+                blocks.append(block)
+                sum = 0
+                count = 0
+                block = datum[0]
+            sum += datum[2]
+            count += 1
+        averages.append(sum / count)
+        blocks.append(block)
+        return averages, blocks
+
+
+def isNewExperiment(row):
+    if len(row) != 1:
+        return False
+    if "benchmark" in row[0]:
+        return True
+    return False
+
+def plotExperiments(experiments, labels=None, title="", ylabel=""):
+    values_count = len(experiments[0].labels) - 1
+    values = []
+    errors = []
+    build_labels = not labels
+    if not labels:
+        labels = []
+    for experiment in experiments:
+        values.append(experiment.getAverages())
+        errors.append(experiment.getErrorRange())
+        if build_labels:
+            labels.append(experiment.name)
+
+    numpy_values = np.asarray(values)
+    numpy_errors = np.asarray(errors)
+    width = 1 / (values_count + 1)
+    numpy_values[0,:] *= 0.1
+    print(numpy_values)
+    print(numpy_values[:,0])
+    for i in range(len(numpy_values[0,:])):
+        print(i, numpy_values[:][i])
+        plt.bar(np.arange(len(numpy_values[:,i])) + i * width, numpy_values[:,i], width=width, yerr=numpy_errors[:,i])
+
+    plt.title("Time measurement overhead")
+    plt.ylabel("microseconds / instructions")
+    if labels:
+        plt.xticks(range(len(values)), labels)
+    plt.show()
+
+"""
+\begin{table}[h!]
+\centering
+\begin{tabular}{||c c c c||} 
+ \hline
+ Col1 & Col2 & Col2 & Col3 \\ [0.5ex] 
+ \hline\hline
+ 1 & 6 & 87837 & 787 \\ 
+ 2 & 7 & 78 & 5415 \\
+ 3 & 545 & 778 & 7507 \\
+ 4 & 545 & 18744 & 7560 \\
+ 5 & 88 & 788 & 6344 \\ [1ex] 
+ \hline
+\end{tabular}
+\caption{Table to test captions and labels}
+\label{table:1}
+\end{table}
+"""
+def convertToTex(experiments):
+    width = len(experiments)
+    height = len(experiments[0].labels)
+    header = " &"
+    # for experiment in experiments:
+
+def graphExperiment(experiment):
+    y, x = experiment.getAveragedData()
+    x = np.asarray(x)
+    y = np.asarray(y)
+    r = np.corrcoef(x, y)
+    print(r)
+    plt.title("Time to read flash")
+    plt.ylabel("milliseconds")
+    plt.xlabel("kb in icache")
+    plt.plot(x/1024, y/10000)
+    plt.show()
+
+
+def processFile(filename, labels=None, special_handler=None, title="", ylabel=""):
+    path_root = sys.argv[0].replace("display_results.py", "")
+    experiment = Experiment()
+    experiments = []
+    with open(path_root + "c/data/{}".format(filename), newline="") as csvfile:
+        for line in csvfile:
+
+            row = line.split(",")
+            if not isNewExperiment(row):
+                experiment.addRow(row)
+            else:
+                if experiment.isValid():
+                    experiments.append(experiment)
+                experiment = Experiment()
+                experiment.addRow(row)
+
+    if experiment.isValid():
+        experiments.append(experiment)
+
+    # plotExperiments(experiments, labels=labels, title=title, ylabel=ylabel)
+    graphExperiment(experiments[0])
+
+processFile("icache.log", labels=["microseconds", "instructions"], title="Time measurement overhead", ylabel="microseconds / instructions")